A Physical Activity and Diet Just-in-Time Adaptive Intervention to Reduce Blood Pressure: The myBPmyLife Study Rationale and Design.

BACKGROUND: Smartphone applications and wearable devices are promising mobile health interventions for hypertension self-management. However, most mobile health interventions fail to use contextual data, potentially diminishing their impact. The myBPmyLife Study is a just-in-time adaptive intervention designed to promote personalized self-management for patients with hypertension. METHODS AND RESULTS: The study is a 6-month prospective, randomized-controlled, remotely administered trial. Participants were recruited from the University of Michigan Health in Ann Arbor, Michigan or the Hamilton Community Health Network, a federally qualified health center network in Flint, Michigan. Participants were randomized to a mobile application with a just-in-time adaptive intervention promoting physical activity and lower-sodium food choices as well as weekly goal setting or usual care. The mobile study application encourages goal attainment through a central visualization displaying participants' progress toward their goals for physical activity and lower-sodium food choices. Participants in both groups are followed for up for 6 months with a primary end point of change in systolic blood pressure. Exploratory analyses will examine the impact of notifications on step count and self-reported lower-sodium food choices. The study launched on December 9, 2021, with 484 participants enrolled as of March 31, 2023. Enrollment of participants was completed on July 3, 2023. After 6 months of follow-up, it is expected that results will be available in the spring of 2024. CONCLUSIONS: The myBPmyLife study is an innovative mobile health trial designed to evaluate the effects of a just-in-time adaptive intervention focused on improving physical activity and dietary sodium intake on blood pressure in diverse patients with hypertension. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05154929.

Identifying Design Opportunities for Adaptive mHealth Interventions That Target General Well-Being: Interview Study With Informal Care Partners.

BACKGROUND: Mobile health (mHealth) interventions can deliver personalized behavioral support to users in daily contexts. These interventions have been increasingly adopted to support individuals who require low-cost and low-burden support. Prior research has demonstrated the feasibility and acceptability of an mHealth intervention app (CareQOL) designed for use with informal care partners. To further optimize the intervention delivery, we need to investigate how care partners, many of whom lack the time for self-care, react and act in response to different behavioral messages. OBJECTIVE: The goal of this study was to understand the factors that impact care partners' decision-making and actions in response to different behavioral messages. Insights from this study will help optimize future tailored and personalized behavioral interventions. METHODS: We conducted semistructured interviews with participants who had recently completed a 3-month randomized controlled feasibility trial of the CareQOL mHealth intervention app. Of the 36 participants from the treatment group of the randomized controlled trial, 23 (64%) participated in these interviews. To prepare for each interview, the team first selected representative behavioral messages (eg, targeting different health dimensions) and presented them to participants during the interview to probe their influence on participants' thoughts and actions. The time of delivery, self-reported perceptions of the day, and user ratings of a message were presented to the participants during the interviews to assist with recall. RESULTS: The interview data showed that after receiving a message, participants took various actions in response to different messages. Participants performed suggested behaviors or adjusted them either immediately or in a delayed manner (eg, sometimes up to a month later). We identified 4 factors that shape the variations in user actions in response to different behavioral messages: uncertainties about the workload required to perform suggested behaviors, concerns about one's ability to routinize suggested behaviors, in-the-moment willingness and ability to plan for suggested behaviors, and overall capability to engage with the intervention. CONCLUSIONS: Our study showed that care partners use mHealth behavioral messages differently regarding the immediacy of actions and the adaptation to suggested behaviors. Multiple factors influence people's perceptions and decisions regarding when and how to take actions. Future systems should consider these factors to tailor behavioral support for individuals and design system features to support the delay or adaptation of the suggested behaviors. The findings also suggest extending the assessment of user adherence by considering the variations in user actions on behavioral support (ie, performing suggested or adjusted behaviors immediately or in a delayed manner). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/32842.

A Community Participatory Approach to Creating Contextually Tailored mHealth Notifications: myBPmyLife Project.

Just-in-time adaptive interventions (JITAIs) are a novel approach to mobile health (mHealth) interventions, sending contextually tailored behavior change notifications to participants when they are more likely to engage, determined by data from wearable devices. We describe a community participatory approach to JITAI notification development for the myBPmyLife Project, a JITAI focused on decreasing sodium consumption and increasing physical activity to reduce blood pressure. Eighty-six participants were interviewed, 50 at a federally qualified health center (FQHC) and 36 at a university clinic. Participants were asked to provide encouraging physical activity and low-sodium diet notifications and provided feedback on researcher-generated notifications to inform revisions. Participant notifications were thematically analyzed using an inductive approach. Participants noted challenging vocabulary, phrasing, and culturally incongruent suggestions in some of the researcher-generated notifications. Community-generated notifications were more direct, used colloquial language, and contained themes of grace. The FQHC participants' notifications expressed more compassion, religiosity, and addressed health-related social needs. University clinic participants' notifications frequently focused on office environments. In summary, our participatory approach to notification development embedded a distinctive community voice within our notifications. Our approach may be generalizable to other communities and serve as a model to create tailored mHealth notifications to their focus population.

Value added? A pragmatic analysis of the routine use of PHQ-9 and GAD-7 scales in primary care.

BACKGROUND: Depression and anxiety are common and often co-occur. The PHQ-9 and GAD-7 scales are frequently used to measure symptoms and track treatment response in these conditions. These instruments show substantial correlation. This study investigates the similarity between concurrent pairs of PHQ-9 and GAD-7 when used to monitor treatment outcomes. METHODS: Data originated from a clinical registry within a behavioral health collaborative care program for a large primary care network. A total of 31,974 pairs of PHQ-9 and GAD-7 scores, from 5402 patient care episodes, were analyzed for correlation coefficient, distribution of score differences, and overlap in symptom burden categories. A Number Needed to Identify was calculated to quantify the marginal effect of performing both scales. RESULTS: The correlation coefficient (Spearman's rho) was 0.74. 78.4% of concurrent scores were within 4 points of each other, and 56.4% of score pairs fell into the same severity class. The Number Needed to Identify for PHQ-9 was 8 while the NNI for GAD-7 was 14.1. CONCLUSIONS: Concurrent pairs of PHQ-9 and GAD-7 were strongly associated and often similar in severity. In terms of identifying clinically significant symptoms, the marginal effect of using both measures appears moderate.

Investigating walking speed variability of young adults in the real world.

BACKGROUND: Walking speed strongly correlates with health outcomes, making accurate assessment essential for clinical evaluations. However, assessments tend to be conducted over short distances, often in a laboratory or clinical setting, and may not capture natural walking behavior. To address this gap, the following questions are investigated in this work: Is walking speed significantly influenced by the continuity and duration of a walking bout? Can preferred walking speed be inferred by grouping walking bouts using duration and continuity? METHODS: We collected two weeks of continuous data from fifteen healthy young adults using a thigh-worn accelerometer and a heart rate monitor. Walking strides were identified and grouped into walking periods. We quantified the duration and the continuity of each walking period. Continuity is used to parameterize changes in stepping rate related to pauses during a bout of walking. Finally, we analyzed the influence of duration and continuity on estimates of stride speed, and examined how the distribution of walking speed varies depending on different walking modes (defined by duration and continuity). RESULTS: We found that continuity and duration can be used to explain some of the variability in real-world walking speed (p<0.001). Speeds estimated from long continuous walks with many strides (42% of all recorded strides) had the lowest standard deviation. Walking speed during these bouts was 1.41ms-1 (SD = 0.26ms-1). SIGNIFICANCE: Walking behavior in the real world is largely variable. Features of real-world walks, like duration and continuity, can be used to explain some of the variability observed in walking speed. As such, we recommend using long continuous walks to confidently isolate the preferred walking behavior of an individual.

Viewing Mobile Health Technology Design Through the Lens of Amplification Theory.

Digital health interventions designed to promote health equity can be valuable tools in the delivery of health care to hardly served patient populations. But if the design of these technologies and the interventions in which they are deployed do not address the myriad structural barriers to care that minoritized patients, patients in rural areas, and patients who have trouble paying for care often face, their impact may be limited. Drawing on our mobile health (mHealth) research in the arena of cardiovascular care and blood pressure management, this viewpoint argues that health care providers and researchers should tend to structural barriers to care as a part of their digital health intervention design. Our 3-step predesign framework, informed by the Amplification Theory of Technology, offers a model that interventionists can follow to address these concerns.

Correction: "Viewing Mobile Health Technology Design Through the Lens of Amplification Theory".

[This corrects the article DOI: 10.2196/31069.].

A Physical Activity Just-in-time Adaptive Intervention Designed in Partnership With a Predominantly Black Community: Virtual, Community-Based Participatory Design Approach.

BACKGROUND: Black people are disproportionally impacted by hypertension. New approaches for encouraging healthy lifestyles are needed to reduce hypertension and promote health equity in Black communities. OBJECTIVE: In this report, we describe the early-stage, virtual design of a just-in-time adaptive intervention (JITAI) to increase physical activity in partnership with members of a low-income, predominantly Black community. METHODS: The hallmark of JITAIs is highly contextualized mobile app push notifications. Thus, understanding participants' context and determinants of physical activity are critical. During the height of the COVID-19 pandemic, we conducted virtual discovery interviews and analysis guided by the Behavior Change Wheel (which focuses on participants' capacity, opportunity, and motivation to engage in physical activity), as well as empathy mapping. We then formed a community-academic participatory design team that partnered in the design sprint, storyboarding, and paper prototyping. RESULTS: For this study, 5 community members participated in the discovery interviews, 12 stakeholders participated in the empathy mapping, 3 community members represented the community on the design team, and 10 community members provided storyboard or paper prototyping feedback. Only one community member had used videoconferencing prior to partnering with the academic team, and none had design experience. A set of 5 community-academic partner design principles were created: (1) keep users front and center, (2) tailor to the individual, (3) draw on existing motivation, (4) make physical activity feel approachable, and (5) make data collection transparent yet unobtrusive. To address community-specific barriers, the community-academic design team decided that mobile app push notifications will be tailored to participants' baseline mobility level and community resources (eg, local parks and events). Push notifications will also be tailored based on the day (weekday versus weekend), time of day, and weather. Motivation will be enhanced via adaptive goal setting with supportive feedback and social support via community-generated notifications. CONCLUSIONS: We completed early-stage virtual design of a JITAI in partnership with community participants and a community design team with limited design and videoconferencing experience. We found that designing JITAIs with the community enables these interventions to address community-specific needs, which may lead to a more meaningful impact on users' health.

Access and attitudinal barriers to engagement in integrated primary care mental health treatment for rural populations.

PURPOSE: Compared to urban areas, rural populations are less likely to engage in mental health care. Using data from the Study to Promote Innovation in Rural Integrated Telepsychiatry, we examined the effect of rurality on engagement in mental health treatment as well as the role of potential mediators. METHODS: Data were obtained from medical records and surveys. We defined rurality using the rural-urban commuting area codes. Baseline mediators included the Endorsed and Anticipated Stigma Inventory and the Assessment of Perceived Access to Care. Engagement outcomes included number of psychotherapy visits and self-reported medication use. We used path analysis to examine the relationship between rurality and engagement and the influence of mediating variables. FINDINGS: Rural participants were less likely to initiate psychotherapy (OR = 0.49; adjusted P = .036), although rurality was not associated with number of psychotherapy sessions or medication use. Rurality was associated with a small elevation in negative beliefs about mental health, but this potential mediator was not associated with engagement. Rurality was negatively associated with lower perceived need for treatment (OR = 0.67, adjusted P = .040), which was in turn positively associated with initiating psychotherapy (OR = 1.99, adjusted P = .001). CONCLUSIONS: Neither rurality itself nor the potential mediators had a large effect on engagement. Federally Qualified Health Centers offering colocated and/or integrated mental health care appear to be mostly mitigating rural-urban disparities in mental health engagement. Improving rates of psychotherapy initiation for rural patients should remain a policy goal.

Developing and Implementing a Cloud-Based Software Solution for Tracking Ureteral Stents: A Pilot Study.

Introduction: As many as 12.5% of patients who undergo ureteral stent placement fail to have their stent removed in a timely manner. Because retained stents can be a source of substantial morbidity, there is a need for solutions to help urologists track their stented patients. Materials and Methods: We developed a cloud-based software that is agnostic to the device manufacturer and can be seamlessly integrated into the electronic health record (EHR). The software automatically registers patients who undergo ureteral stent placement and then follows them through their postoperative course to ensure timely follow-up for device removal. To validate our software's performance, we reviewed the medical records of patients who underwent stent placement for any indication at our institution between February 1, 2018, and February 28, 2018. Results: During our 1-month pilot study, a total of 51 ureteral stents were placed during 49 procedures that were performed on 46 patients. Our software effectively captured all of these procedures. It was able to properly distinguish 31 procedures where the patient who underwent stenting had follow-up scheduled before surgery. More importantly, it alerted our schedulers to 18 procedures for which no return visit had been scheduled. Furthermore, our software was able to register follow-up attendance, correctly identifying 10 procedures where patients failed to arrive. Conclusion: We describe a high-fidelity software solution for automated tracking of ureteral stents that is agnostic to the device manufacturer and can be seamlessly integrated into the EHR, causing minimal disruption to provider workflows.

Estimating Walking Speed in the Wild.

An individual's physical activity substantially impacts the potential for prevention and recovery from diverse health issues, including cardiovascular diseases. Precise quantification of a patient's level of day-to-day physical activity, which can be characterized by the type, intensity, and duration of movement, is crucial for clinicians. Walking is a primary and fundamental physical activity for most individuals. Walking speed has been shown to correlate with various heart pathologies and overall function. As such, it is often used as a metric to assess health performance. A range of clinical walking tests exist to evaluate gait and inform clinical decision-making. However, these assessments are often short, provide qualitative movement assessments, and are performed in a clinical setting that is not representative of the real-world. Technological advancements in wearable sensing and associated algorithms enable new opportunities to complement in-clinic evaluations of movement during free-living. However, the use of wearable devices to inform clinical decisions presents several challenges, including lack of subject compliance and limited sensor battery life. To bridge the gap between free-living and clinical environments, we propose an approach in which we utilize different wearable sensors at different temporal scales and resolutions. Here, we present a method to accurately estimate gait speed in the free-living environment from a low-power, lightweight accelerometer-based bio-logging tag secured on the thigh. We use high-resolution measurements of gait kinematics to build subject-specific data-driven models to accurately map stride frequencies extracted from the bio-logging system to stride speeds. The model-based estimates of stride speed were evaluated using a long outdoor walk and compared to stride parameters calculated from a foot-worn inertial measurement unit using the zero-velocity update algorithm. The proposed method presents an average concordance correlation coefficient of 0.80 for all subjects, and 97% of the error is within ±0.2m· s -1. The approach presented here provides promising results that can enable clinicians to complement their existing assessments of activity level and fitness with measurements of movement duration and intensity (walking speed) extracted at a week time scale and in the patients' free-living environment.

Real-World Use and Self-Reported Health Outcomes of a Patient-Designed Do-it-Yourself Mobile Technology System for Diabetes: Lessons for Mobile Health.

BACKGROUND: The aim of this study is to compare demographic/disease characteristics of users versus nonusers of a do-it-yourself (DIY) mobile technology system for diabetes (Nightscout), to describe its uses and personalization, and to evaluate associated changes in health behaviors and outcomes. METHODS: A cross-sectional, household-level online survey was used. Of 1268 household respondents who were members of the CGM in the Cloud Facebook group, there were 1157 individuals with diabetes who provided information about Nightscout use. RESULTS: The majority of individuals with diabetes in the household sample were 6-12 years old (followed by 18 years and above, and 13-17 years), non-Hispanic whites (90.2%), with type 1 diabetes (99.4%). The majority used an insulin pump (85.6%) and CGM (97.0%) and had private health insurance (83.8%). Nightscout use was more prevalent among children compared with adolescents and adults. Children used Nightscout for nighttime, school, sporting events, and travel; adults used it for nighttime, work, travel, and sporting events. Whereas the majority of adults viewed their own data without assistance from others, among pediatric users, a median of three individuals (range: 0-8) viewed Nightscout, with a median of three devices per viewer (range: 0-7). Individuals reported that after Nightscout adoption, they checked blood glucose values with a meter less often; bolused more frequently; gave more boluses without checking first with a blood glucose meter; and experienced significant improvements in HbA1c and quality of life. CONCLUSIONS: The Nightscout Project is a patient-driven mobile technology for health and may have beneficial effects on glycemic control and quality of life.

Predicting delirium: a review of risk-stratification models.

BACKGROUND: Delirium is a common condition in hospitalized patients and is associated with multiple adverse outcomes. There is increasing evidence to support interventions that prevent delirium, so the identification of patients at high risk is of significant clinical value. Numerous risk factors have been identified, including both premorbid patient characteristics and acute precipitants. Despite this, predicting the occurrence of delirium remains a clinical challenge. OBJECTIVE: This article reviews studies of validated risk-stratification models for delirium. We discuss possible barriers to use of these models and future directions for research. METHODS: A comprehensive review of the literature was completed using PubMed and Embase. The resulting citations were filtered in a structured process. Inclusion criteria were original research, adult medical inpatient population and presence of a validation group in the study design. RESULTS: Ten cohort studies met inclusion criteria. The quality of the studies was moderate to good. All studies proposed models using clinical data to predict the risk of patients' developing delirium. CONCLUSION: The most common risk factors identified were preexisting cognitive impairment, medical comorbidity, elevated Blood Urea Nitrogen, and impairment in activities of daily living. While multiple validated predictive models exist, there is substantial heterogeneity between models, and only one replication study has been performed. In addition, difficulties in implementation may be a barrier to broader use of these models. There is limited support for an accurate and reliable tool to predict inpatient delirium. Further research is needed in this clinically important area.

Using online peer-mentoring to empower young adults with end-stage renal disease: a feasibility study.

Patients with end-stage renal disease must receive a kidney transplant or live on dialysis. Either treatment option introduces radical changes to their lifestyles and may result in significant psychosocial disruptions. Among these patients, young adults (YAs)-between age 18 and 30-are confronted with unique challenges because their life course is yet to be defined and their adulthood identity has not fully emerged. Partnering with the National Kidney Foundation of Michigan, we experimented with a web-based "peer-mentoring" intervention to create a user-driven, self-sustained online community. The objective was to help YAs develop "new normal" lives, restore social identities, and regain confidence in school and work. To foster a comforting online atmosphere for this vulnerable population, it is critical to use tailored technology designs catering to their needs and concerns. In this paper, we describe a prototype that we developed-ktalk.org, and report our findings from pilot-testing it with 38 YAs.